Composition design and characterization of alkali-activated Slag–Metakaolin materials

Abstract

This study explores the effects of the interactions among Na2O content, metakaolin content and activator modulus on the compressive strength and autogenous shrinkage of alkali-activated slag–metakaolin (AASM) materials. The Box–Behnken RSM design was used to create an experimental scheme, establish a model, and optimize the mix proportions. Fourier transform infrared spectroscopy, scanning electron microscopy, and Mercury intrusion experiments were used to analyze the compositions, microstructures, and pore structures of the hydration products of the AASM, respectively. Results showed that the interactions between the activator modulus and metakaolin content, as well as Na2O content and metakaolin content, are the key factors affecting the compressive strength and autogenous shrinkage, respectively, of the AASM. Under the optimal conditions of Na2O content of 6%, sodium silicate modulus of 1.5, and metakaolin/slag ratio of 1: 3, the relative errors in the model verification test for compressive strength and autogenous shrinkage are 0% and 0.18%, respectively. In the water glass modulus and metakaolin content interaction, Ca2+, A13+, and Si4+ ions in the composite system react with several [SiO4]4− groups to form C-A-S-H and N-A-S-H gels, which fill each other to make the composite structure denser. When Na2O interacts with metakaolin, the OH− and Na+ in the solution react with A13+ and Si4+ to generate additional N-A-S-H, thereby reducing the compressive strength of the composite system, mitigating autogenous shrinkage, and increasing volume stability.

Prediction Model Based on DoE and FTIR Data to Control Fast Setting and Early Shrinkage of Alkaline-Activated Slag/Silica Fume Blended Cementitious Material

“…However, the stretch bonds are optimal for drawing conclusions about the material properties, which are affected by the microstructure. The changes in the bonds affect the flexibility of the structure (e.g., shape changes), linking directly to the gel structure [72]. FTIR analysis can thus be used to obtain information on changes in microstructure inexpensively, much more efficiently, and quickly.…”

“…A single-factor method used in other relevant studies cannot reflect the interaction between different factors. Thus, response surface models (RSM) were often chosen to predict and evaluate strength trends [72,73]. In these studies, the prediction models were always based on the activator composition in terms of the modulus of the activator, the choice of activator, and the content of binder.…”